Abstract
Proof of Work (PoW) is the pioneering consensus mechanism that underpins the security and operation of many public blockchain networks, incl
Smart Contracts: Automating Trust in Decentralized Systems
Posted on by Fachrur Rozi
Abstract
Smart contracts are self-executing digital agreements written in code and deployed on decentralized platforms such as blockchain networks. B
Consensus Mechanisms in Decentralized Systems
Posted on by Fachrur Rozi
Abstract
Consensus mechanisms are the backbone of decentralized systems, enabling distributed nodes to agree on a single version of truth without rel
Decentralized Ledger Technology (DLT): Future Directions
Posted on by Fachrur Rozi
Abstract
Decentralized Ledger Technology (DLT) represents a paradigm shift in how data is recorded, verified, and shared across networks. Unlike trad
Blockchain Integration in the IoT: Secure Machine Communication
Posted on by Fachrur Rozi
Abstract
The convergence of Blockchain and the Internet of Things (IoT) is reshaping how devices interact, share data, and build trust in a decentral
Regulatory and Legal Challenges in Blockchain Technology
Posted on by Fachrur Rozi
Abstract
Blockchain technology has revolutionized the digital landscape by offering decentralization, immutability, and transparency. While these fea
Model Interpretability in ML: Bridging Performance and Trust
Posted on by Fachrur Rozi
Abstract
The increasing deployment of machine learning (ML) systems in high-stakes applications has amplified the demand for model interpretability.
Bias and Fairness in Artificial Intelligence: A Deep Dive into EML
Posted on by Fachrur Rozi
Introduction
As machine learning (ML) and artificial intelligence (AI) systems become increasingly integrated into daily life—from loan approva
Universitas Medan Area (UMA) Resmi Luncurkan Pendaftaran Mahasiswa Baru 2025/2026
Posted on by Fachrur Rozi
Universitas Medan Area (UMA) secara resmi meluncurkan Pendaftaran dan Informasi Mahasiswa Baru (PIMB) untuk tahun akademik 2025/2026. Acara peluncuran
Resampling Techniques for Imbalanced Data
Posted on by Fachrur Rozi
Introduction
Resampling techniques are one of the most effective ways to handle class imbalance in machine learning. These methods modify the dataset
